Transformative Advances

Over the past decade, machine learning has enabled transformative advances in physical security technology. We have seen some amazing progress in using machine learning algorithms to train computers to assess and improve computational processes. Although such tools are helpful for security and operations, machines are still far from being capable of thinking or acting like humans. They do, however, offer unique opportunities for teams to enhance security and productivity.

Opportunities in Security and Operations
In physical security, machine learning can speed up investigations by assisting security teams in finding relevant information quickly. Machine learning helps analyze data that hasn’t been organized or labeled. By identifying patterns or possible relationships between data, such tools help security teams, law enforcement, and other staff gain a better understanding of an incident or important correlations between trends.

On the operations side, machine learning helps organizations better leverage their physical security investments. Machine learning can help glean actionable insights from the system data to ramp up productivity. This often leads to improved operations.

For example, machine learning can help automate people counting, monitor traffic flow and enhance cybersecurity by identifying and blocking malware. It can also enable automation that helps organizations adhere to various industry standards and regulations through streamlined processes.

Deep Learning to Structure Data
One type of machine learning that has been particularly influential in the physical security world is deep learning. It uses task-specific algorithms to train computers to classify data.

Programmers begin with data sets that have been carefully organized or labeled. Then deep learning tools take unstructured data, such as hours of video footage, and turn it into structured data. The computer recognizes matching patterns or correlations that it can apply to other instances. As a result, teams can more easily find the specific items or events they are looking for.

For example, modern video analytics systems may use deep learning to “read” the letters and numbers on license plates. Other teams may use the tools to count how many people pass through a door or pick out a certain model of a car that passed by on a busy road. An operator can ask the system to display video that includes a red truck with a specific license plate or a person wearing blue jeans, a plaid shirt, and a brown baseball cap. Quickly sorting through data helps speed up processes and allows teams to operate more efficiently.

Combining Video Analytics with Automation
Using machine learning, systems can compile data from cameras and use video analytics to detect specific activities or items. Then, through automation techniques, the system can respond in certain ways if such an event occurs.

For example, when an intruder is detected, the system is programmed to alert the security team. Video and sensor data help track the intruder’s progress on a map, so responders find them more easily. The system may take additional actions, such as locking interior doors and notifying law enforcement. Throughout the process, it is important to note that every action follows criteria established by the programmers who set up these workflows in the system. The automation tools simply follow the steps based on the inputs received and identified.

Unification, Privacy and Human-centered Design at the Core
Unified physical security systems that leverage machine learning can collect and interpret a wide variety of data from many sources. Likewise, open architecture systems give security professionals the freedom to explore applications from various manufacturers. As new solutions come to market, teams can try them out and select the ones that best fit their objectives and environment.

Regardless of the applications selected, it is important to use the technology in ethical ways. Confirm with your manufacturer that the data your deep learning system is trained on is properly sourced and allowed to be used. People must give consent, and the manufacturer should ensure their right to privacy is respected.

While machine learning has come a long way in the last few decades, it is important to remember that it is not magic. To be useful, machine learning technology must be combined with human-centered design that is grounded in real-world customer problems.

When exploring options, begin by clearly identifying the challenges you want to address or the outcomes you seek. Then explore if machine learning is the right tool for that. It is not about simply implementing the latest application but understanding how that solution will impact your goals.

Likewise, humans need to be the final decision-makers and confirm that best practices are in place in all situations. While machine learning systems can streamline processes, sort through data, and help ensure procedures are properly followed, they do not replace human expertise.

This article originally appeared in the July / August 2024 issue of Security Today.

Featured

  • Pragmatism, Productivity, and the Push for Accountability in 2025-2026

    Every year, the security industry debates whether artificial intelligence is a disruption, an enabler, or a distraction. By 2025, that conversation matured, where AI became a working dimension in physical identity and access management (PIAM) programs. Observations from 2025 highlight this turning point in AI’s role in access control and define how security leaders are being distinguished based on how they apply it. Read Now

  • Report: Cyber Attackers Continue to Turn to AI-Based Tools to Avoid Detection

    Comcast Business recently released its 2025 Cybersecurity Threat Report, a comprehensive analysis of 34.6 billion cybersecurity events detected between June 1,2024 and May 31, 2025. Now in its third year, the report offers business leaders a unique perspective into the evolving threat landscape and provides actionable insights to help organizations strengthen their defenses and align cybersecurity with business risk. Read Now

  • Axis Communications Creates AI-powered Video Surveillance Orchestra

    What if cameras could not only see the world, but interpret it—and respond like orchestra musicians reading sheet music: instantly, precisely, and in perfect harmony? That’s what global network technology leader Axis Communications set to find out. Read Now

  • Just as Expected

    GSX produced a wonderful tradeshow earlier this week. Monday was surprisingly strong in the morning, and the afternoon wasn’t bad at all. That’s Monday’s results and asking attendees to travel on Sunday. Just a quick hint, no one wants to give up their weekend to travel and set up an exhibit booth. I’m just saying. Read Now

    • Industry Events
    • GSX
  • NOLA: The Crescent City

    Twenty years later we finds ourselves in New Orleans. Twenty years ago the aftermath of Hurricane Katrina forced exhibitors and attendees to look elsewhere for tradeshow floor space. Read Now

    • Industry Events
    • GSX

New Products

  • Mobile Safe Shield

    Mobile Safe Shield

    SafeWood Designs, Inc., a manufacturer of patented bullet resistant products, is excited to announce the launch of the Mobile Safe Shield. The Mobile Safe Shield is a moveable bullet resistant shield that provides protection in the event of an assailant and supplies cover in the event of an active shooter. With a heavy-duty steel frame, quality castor wheels, and bullet resistant core, the Mobile Safe Shield is a perfect addition to any guard station, security desks, courthouses, police stations, schools, office spaces and more. The Mobile Safe Shield is incredibly customizable. Bullet resistant materials are available in UL 752 Levels 1 through 8 and include glass, white board, tack board, veneer, and plastic laminate. Flexibility in bullet resistant materials allows for the Mobile Safe Shield to blend more with current interior décor for a seamless design aesthetic. Optional custom paint colors are also available for the steel frame.

  • FEP GameChanger

    FEP GameChanger

    Paige Datacom Solutions Introduces Important and Innovative Cabling Products GameChanger Cable, a proven and patented solution that significantly exceeds the reach of traditional category cable will now have a FEP/FEP construction.

  • QCS7230 System-on-Chip (SoC)

    QCS7230 System-on-Chip (SoC)

    The latest Qualcomm® Vision Intelligence Platform offers next-generation smart camera IoT solutions to improve safety and security across enterprises, cities and spaces. The Vision Intelligence Platform was expanded in March 2022 with the introduction of the QCS7230 System-on-Chip (SoC), which delivers superior artificial intelligence (AI) inferencing at the edge.